A wireless communication device in a communication system communicates directly or indirectly with other wireless communication devices. For direct/point-to-point communications, the participating wireless communication devices tune their receivers and transmitters to the same channel(s) and communicate over those channels. For indirect wireless communications, each wireless communication device communicates directly with an associated base station and/or access point via an assigned channel.
Each wireless communication device participating in wireless communications includes a built-in radio transceiver (i.e., transmitter and receiver) or is coupled to an associated radio transceiver. Typically, the transmitter includes one antenna for transmitting radiofrequency (RF) signals, which are received by one or more antennas of the receiver. When the receiver includes two or more antennas, the receiver selects one of antennas to receive the incoming RF signals. This type of wireless communication between the transmitter and receiver is known as a single-output-single-input (SISO) communication.
Well known communications system provide a range extension on a SISO system by reducing the data rate and, as a result, increase the symbol duration and/or increasing transmit power. However, increasing transmit power can lead to increase interference to other users sharing the network. The preferred method for improved range reception does not lead to decreased network capacity. For popular multicarrier systems such as SISO WLANs, range improvement is achieved by taking an 802.11a/802.11g signal and cutting the symbol rate. Specifically, the current communications system achieves range extension by dividing a symbol clock by 24, i.e., the inverse of Super-G, which doubles the clock frequency. When the symbol clock is divided, the maximum symbol duration is 96 usec and the corresponding rate is 250 kbps. For example, the current communications system takes an 802.11a/802.11g signal that is 16.5 MHz, divides the symbol clock by 24 and cuts the signal to 687.5 kHz. When the bandwidth for a signal is reduced, the integrated thermal noise density of the receiver is also reduced. Therefore, when the bandwidth is reduced by a factor of 24, the thermal noise floor is decreased by 10*log 10(24). This results in a 13 dB “gain” in the sensitivity of the receiver which is equivalent to at least 3 times improvement in the range of a typical wireless system. The cost of this implementation, however, is that the data rate is also decreased by a factor of 24. What is needed is a communication device, system and method that increases the transmission range of a WLAN without reducing the data rate. A suitable invention would improve transmission characteristics without data rate reduction or increased interference at the expense of bandwidth expansion of the wireless system.
Generally speaking, transmission systems compliant with the IEEE 802.11a and 802.11g or “802.11a/g” as well as the 802.11n standards achieve their high data transmission rates using Orthogonal Frequency Division Modulation (OFDM) encoded symbols mapped up to a 64 quadrature amplitude modulation (QAM) multi-carrier constellation. In a general sense, the use of OFDM divides the overall system bandwidth into a number of frequency sub-bands or channels, with each frequency sub-band being associated with a respective sub-carrier upon which data may be modulated. Thus, each frequency sub-band of the OFDM system may be viewed as an independent transmission channel within which to send data, thereby increasing the overall throughput or transmission rate of the communication system. Similarly, multi-code spread spectrum system comprised of perfectly orthogonal high-speed chaos spreading codes transporting independent modulated data can be used to increase its overall throughput or transmission rate of the SISO system. The high-speed “spreading signals” belong to the class of signals referred to as Pseudo Noise (PN) or pseudo-random signal. This class of signals possesses good autocorrelation and cross-correlation properties such that different PN sequences are nearly orthogonal to one other. The autocorrelation and cross-correlation properties of these PN sequences allow the original information bearing signal to be spread at the transmitter.
Transmitters used in the wireless communication systems that are compliant with the aforementioned 802.11a/802.11g/802.11n standards as well as other standards such as the 802.16a IEEE Standard, typically perform multi-carrier OFDM symbol encoding (which may include error correction encoding and interleaving), convert the encoded symbols into the time domain using Inverse Fast Fourier Transform (IFFT) techniques, and perform digital to analog conversion and conventional radio frequency (RF) upconversion on the signals. These transmitters then transmit the modulated and upconverted signals after appropriate power amplification to one or more receivers, resulting in a relatively high-speed time domain signal with a high peak-to-average ratio (PAR).
Transmitters used in direct sequence spread spectrum (DSSS) wireless communication systems such as those compliant with commercial telecommunication standards WCDMA and CDMA 2000 perform high-speed spreading of data bits after error correction, interleaving and prior to symbol mapping. Thereafter, the digital signal is converted to analog form and frequency translated using conventional RF upconversion methods. The combined signals for all DSSS signals are appropriately power amplified and transmitted to one or more receivers.
Likewise, the receivers used in the wireless communication systems that are compliant with the aforementioned 802.11a/802.11g/802.11n and 802.16a IEEE standards typically include an RF receiving unit that performs RF downconversion and filtering of the received signals (which may be performed in one or more stages), and a baseband processor unit that processes the OFDM encoded symbols bearing the data of interest. The digital form of each OFDM symbol presented in the frequency domain is recovered after baseband downconverting, conventional analog to digital conversion and Fast Fourier Transformation of the received time domain signal. Whereas receivers used for reception for DSSS must de-spread the high signal after baseband downconverting to restore the original information signal band but yields a processing gain equal to the ratio the high speed signal to information bearing signal. Thereafter, the baseband processor performs demodulation and frequency domain equalization (FEQ) to recover the transmitted symbols, and these symbols are then processed with an appropriate FEC decoder, e.g. a Viterbi decoder, to estimate or determine the most likely identity of the transmitted symbol. The recovered and recognized stream of symbols is then decoded, which may include deinterleaving and error correction using any of a number of known error correction techniques, to produce a set of recovered signals corresponding to the original signals transmitted by the transmitter.
To further increase the number of signals which may be propagated in the communication system and/or to compensate for deleterious effects associated with the various propagation paths, and to thereby improve transmission performance, it is known to use multiple transmission and receive antennas within a wireless transmission system. Such a system is commonly referred to as a multiple-input, multiple-output (MIMO) wireless transmission system and is specifically provided for within the 802.11n IEEE Standard now being adopted. As is known, the use of MIMO technology produces significant increases in spectral efficiency, throughput and link reliability, and these benefits generally increase as the number of transmission and receive antennas within the MIMO system increases.
In particular, in addition to the frequency channels created by the use of OFDM, a MIMO channel formed by the various transmissions and receive antennas between a particular transmitter and a particular receiver includes a number of independent spatial channels. As is known, a wireless MIMO communication system can provide improved performance (e.g., increased transmission capacity) by utilizing the additional dimensionalities created by these spatial channels for the transmission of additional data. Of course, the spatial channels of a wideband MIMO system may experience different channel conditions (e.g., different fading and multi-path effects) across the overall system bandwidth and may therefore achieve different signal-to-noise ratio (SNRs) at different frequencies (i.e., at the different OFDM frequency sub-bands) of the overall system bandwidth. Consequently, the number of information bits per modulation symbol (i.e., the data rate) that may be transmitted using the different frequency sub-bands of each spatial channel for a particular level of performance may differ from frequency sub-band to frequency sub-band. Whereas DSSS signal occupies the entire channel band, the number of information bits per modulation symbol (i.e., the data rate) that may be transmitted using the different chaos sequence for each spatial channel for a particular level of performance.
In the MIMO-OFDM communication system using a typical scheme, a high Peak-to-Average Power Ratio (PAPR) may be caused by the multiple carrier modulation. That is, because data are transmitted using multiple carriers in the MIMO-OFDM scheme, the final OFDM signals have amplitude obtained by summing up amplitudes of each carrier. The high PAPR results when the carrier signal phases are added constructively (zero phase difference) or destructively (±180 phase difference). Notably, OFDM signals have a higher peak-to-average ratio (PAPR) often called a peak-to-average power ratio (PAPR) than single-carrier signals do. The reason is that in the time domain, a muiticarrier signal is the sum of many narrowband signals. At some time instances, this sum is large and at other times is small, which means that the peak value of the signal is substantially larger than the average value. Similarly, MIMO-DSSS schemes can have high PAPR for periodic sequence or binary-valued sequence; however chaos spreading sequences do not exhibit either of these characteristics and therefore have better PAPR performance for SISO and MIMO operations.
The continually increasing reliance on SISO and especially MISO wireless forms of communication creates reliability and privacy problems. Data should be reliably transmitted from a transmitter to a receiver. In particular, the communication should be resistant to noise, interference, and possibly to interception by unintended parties.
In the last few years there has been a rapidly growing interest in ultra-wide bandwidth (UWB) impulse radio (IR) communication systems. These systems make use of ultra-short duration pulses that yield ultra-wide bandwidth signals characterized by extremely low power spectral densities. UWB-IR systems are particularly promising for short-range wireless communications as they combine reduced complexity with low power consumption, low probability of detection (LPD), immunity to multipath fading, and multi-user capabilities. Current UWB-IR communication systems employ pseudo-random noise (PN) coding for channelization purposes and pulse-position modulation (PPM) for encoding the binary information.
Others have proposed a periodic sequences of pulses in the context of chaos-based communication system. Additional work has relied upon the self-synchronizing properties of two chaotic systems. In such a system, data is modulated into pulse trains using variable time delays and is decodable by a coherent receiver having a chaotic generator matched to the generator used in the transmitter. Such system is known in the art as a Chaotic Pulse Position Modulation (CPPM) scheme.
Such chaotic dynamical systems have been proposed to address the problem of communication privacy. Chaotic signals exhibit a broad continuous spectrum and have been studied in connection with spread-spectrum applications. The irregular nature of a chaotic signal makes it difficult to intercept and decode. In many instances a chaotic signal will be indistinguishable from noise and interference to receivers not having knowledge of the chaotic signal used for transmission. In the context of UWB systems the use of non-periodic (chaotic) codes enhances the spread-spectrum characteristics of the system by removing the spectral features of the signal transmitted. This results in a lower probability of interception/detection (LPI/LPD) and possibly less interference towards other users. This makes the chaos-based communication systems attractive.
There remains a need for improved chaotic coding/modulation methods to produce such attractive communication systems. One prior art, U.S. Pat. No. 6,882,689, issued Apr. 15, 2005 to Maggio et al., attempts to improve chaotic coding using pseudo-chaotic coding/modulation method that exploits the symbolic dynamics of a chaotic map at the transmitter to encode data. The method uses symbolic dynamics as “coarse-grained” description of the evolution of a dynamic system. The state space is partitioned and a symbol is associated with each partition. The Maggio invention uses a trajectory of the dynamic system and analyzes it as a symbolic system. A preferred transmitter of the Maggio prior art accepts digital data for coding and the digital data is allocated to symbolic states according to a chaotic map using a shift register to approximate the Bernoulli shift map acting as a convolution code with a number of states equal to the symbolic states defined on the chaotic map. The pseudo-chaotically coded data is converted to analog form and modulated into synchronization frames in a transmitted signal.
The Maggio prior art has limitations in that it uses only one chaos map (e.g., Bernoulli shift map) that is generated based on the data transmitted. By confining the mapping to Bernoulli shift, information that is repeated in each transmission or repeat symbol can be recognized after observing the waveform over an extended period of time. Once compromised, all future data will be detectable and decodable by a hostile system.
Generally, the most fundamental issue in wireless communication lies in how efficiently and reliably data can be transmitted through a channel. The next generation multimedia mobile communication system, which has been actively researched in recent years, requires a high speed communication system capable of processing and transmitting various forms of information such as images and wireless data, different than an initial communication system providing a voice-based service.
Then according to the prior art, what is needed is a system and method that does not sacrifice data rate in favor of range, provides increased robustness, while improving LPI/LPD.